Microelectromechanical system (MEMS) sensors have recently been integrated within mobile devices to provide acceleration measurements for identifying movement. “Stationarity” of the mobile device (e.g., sitting unattended on a nightstand or desk) may be inferred from triaxial MEMS accelerometer signals when the acceleration change measured on all axes is insignificant. This type of movement detection operates independently from environmental RF signals, including those based on signals from wireless wide-area networks and local-area networks, as well as satellite or global positioning systems, and offers a way of optimizing cell phone performance if movement information is provided efficiently and accurately.
However, problems arise with conventional MEMS stationarity detection schemes because they tend to indicate movement when the device is “fidgeting,” such as when the device is attached to a person's belt while sitting in a meeting or being held in a person's hand while standing conversing with a colleague, even though the mobile device is moving at low or near zero average velocity.